Feature Engineering Made Easy

Keeping the top k eigenvalues (sorted by the descending eigenvalues)

Now that we have our four eigenvalues, we will choose the appropriate number of them to keep to consider them principal components. We can choose all four if we wish, but we generally wish to choose a number less than the original number of features. But what is the right number? We could grid search and find the answer using the brute-force method, however, we have another tool in our arsenal, called the scree plot.

A scree plot is a simple line graph that shows the percentage of total variance explained in the data by each principal component. To build this plot, we will sort the eigenvalues in order of descending value and plot the cumulative variance explained by each ...